| 1. |
- Andersen, Martin, et al.
(author)
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Distributed Robust Stability Analysis of Interconnected Uncertain Systems
- 2012
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In: Proceedings of the 51st IEEE Conference on Decision and Control. - 0743-1546. - 9781467320641 - 9781467320658 ; , s. 1548-1553
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Conference paper (peer-reviewed)abstract
- This paper considers robust stability analysis of a large network of interconnected uncertain systems. To avoid analyzing the entire network as a single large, lumped system, we model the network interconnections with integral quadratic constraints. This approach yields a sparse linear matrix inequality which can be decomposed into a set of smaller, coupled linear matrix inequalities. This allows us to solve the analysis problem efficiently and in a distributed manner. We also show that the decomposed problem is equivalent to the original robustness analysis problem, and hence our method does not introduce additional conservativeness.
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| 2. |
- Chen, Tianshi, et al.
(author)
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Sparse multiple kernels for impulse response estimation with majorization minimization algorithms
- 2012
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In: Decision and Control (CDC), 2012. - : IEEE. - 9781467320658 - 9781467320641 ; , s. 1500-1505
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Conference paper (peer-reviewed)abstract
- This contribution aims to enrich the recently introduced kernel-based regularization method for linear system identification. Instead of a single kernel, we use multiple kernels, which can be instances of any existing kernels for the impulse response estimation of linear systems. We also introduce a new class of kernels constructed based on output error (OE) model estimates. In this way, a more flexible and richer representation of the kernel is obtained. Due to this representation the associated hyper-parameter estimation problem has two good features. First, it is a difference of convex functions programming (DCP) problem. While it is still nonconvex, it can be transformed into a sequence of convex optimization problems with majorization minimization (MM) algorithms and a local minima can thus be found iteratively. Second, it leads to sparse hyper-parameters and thus sparse multiple kernels. This feature shows the kernel-based regularization method with multiple kernels has the potential to tackle various problems of finding sparse solutions in linear system identification.
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| 3. |
- Hostettler, Roland, et al.
(author)
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Extended Kalman filter for vehicle tracking using road surface vibration measurements
- 2013
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In: IEEE 51st Annual Conference on Decision and Control. - Piscataway, NJ : IEEE Communications Society. - 9781467320658 - 9781467320641
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Conference paper (peer-reviewed)abstract
- This paper addresses a novel method for vehicle tracking using an extended Kalman filter and measurements of road surface vibrations from a single accelerometer. First, a measurement model for vibrations caused by vehicular road traffic is developed. Then the identifiability of the involved parameters is analyzed. Finally, the measurement model is combined with a constant speed motion model and the Kalman filter is derived. Simulation and measurement results indicate that the approach is feasible and show where further development is needed.
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| 4. |
- Lyzell, Christian, et al.
(author)
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A Convex Relaxation of a Dimension Reduction Problem Using the Nuclear Norm
- 2012
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In: Proceedings of the 51st IEEE Conference on Decision and Control. - 9781467320641 - 9781467320658 ; , s. 2852-2857
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Conference paper (peer-reviewed)abstract
- The estimation of nonlinear models can be a challenging problem, in particular when the number of available data points is small or when the dimension of the regressor space is high. To meet these challenges, several dimension reduction methods have been proposed in the literature, where a majority of the methods are based on the framework of inverse regression. This allows for the use of standard tools when analyzing the statistical properties of an approach and often enables computationally efficient implementations. The main limitation of the inverse regression approach to dimension reduction is the dependence on a design criterion which restricts the possible distributions of the regressors. This limitation can be avoided by using a forward approach, which will be the topic of this paper. One drawback with the forward approach to dimension reduction is the need to solve nonconvex optimization problems. In this paper, a reformulation of a well established dimension reduction method is presented, which reveals the structure of the optimization problem, and a convex relaxation is derived.
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| 5. |
- Simon, Daniel, et al.
(author)
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Reference Tracking MPC using Terminal Set Scaling
- 2012
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In: Proceedings of the 51st IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 9781467320658 - 9781467320641 ; , s. 4543-4548
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Reports (other academic/artistic)abstract
- A common assumption when proving stability of linear MPC algorithms fort racking applications is to assume that the desired setpoint is located farinto the interior of the feasible set. The reason for this is that the terminal state constraint set which is centered around the setpoint must be contained within the feasible set. In many applications this assumption can be severly limiting since the terminal set is relatively large and therefore limits how close the setpoint can be to the boundary of the feasible set. We present simple modifications that can be performed in order to guarantee stability and convergence to setpoints located arbitrarily close to the boundary of the feasible set. The main idea is to introduce a scaling variable which dynamically scales the terminal state constraint set and therefore allowsa setpoint to be located arbitrarily close to the boundary. In addition to this the concept of pseudo setpoints are used to gain the maximum possible region of attraction and to handle infeasible references. Recursive feasibility and convergence to the desired setpoint, or its closest feasible alternative, is proven and a motivating example of controlling an agile fighter aircraftis given.
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| 6. |
- Sjöberg, Johan, et al.
(author)
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Interactive Multiobjective Optimization for the Hot Rolling Process
- 2012
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In: Proceedings of 51st IEEE Conference on Decision and Control<em></em>. - 9781467320641 - 9781467320658 ; , s. 7030-7036
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Conference paper (peer-reviewed)abstract
- In this paper, multi-objective optimization is applied to the hot rolling process. It is modeled mostly using first principle models considering, for instance, the mass balance (or mass flow rate), the tensions in the material, the power requirements, the thermal field, and the microstructure of the material.Two optimization formulations are considered. In the first case, both the grain size and the power consumption in the rolling process are minimized. It is shown that the result from a single-objective optimization formulation, i.e., where only one of the two objectives are considered, yields control schedules with poor performance for the other objective. Furthermore, the differences between optimal control schedules for different objectives are compared and analyzed. The second case is a design optimization problem where the optimal positioning of cooling pipes is considered. This study shows how the MOO framework can be used to systematically choose a good cooling pipe setup. The two studies shows that MOO can be a helpful tool when designing and running hot rolling processes. Furthermore, navigation among the Pareto optimal solutions is very useful when the user wants to learn how the control variables interact with the process.
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| 7. |
- Ali, Mohammad, 1982, et al.
(author)
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Threat assessment design under driver parameter uncertainty
- 2012
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In: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. - 9781467320641 ; , s. 6315-6320
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Conference paper (peer-reviewed)abstract
- We consider a model-based threat assessment method, which enables the activation of assisting safety interventions in case an accident threat to the driver is detected. The method relies on vehicle and driver mathematical models and reachability analysis tools. In particular, we focus on the problem of false threats detection that can occur due to uncertainties in the driver model, i.e., the driver is incorrectly deemed incapable of accomplishing a driving task. This paper proposes a novel approach, to compensate for uncertainties in the driver model, for the considered threat assessment method. In particular, we show how the considered threat assessment method can be designed such that, if a threat is detected, the driver is guaranteed to be unable to perform the assigned driving task. In such case, an automated assisting intervention can be motivated
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| 8. |
- Andersson, Joel, et al.
(author)
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Dynamic optimization with CasADi
- 2012
-
In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - 0743-1546. - 9781467320658 ; , s. 681-686
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Conference paper (peer-reviewed)abstract
- We demonstrate how CasADi, a recently devel- oped, free, open-source, general purpose software tool for nonlinear optimization, can be used for dynamic optimization in a flexible, interactive and numerically efficient way. CasADi is best described as a minimalistic computer al- gebra system (CAS) implementing automatic differentiation (AD) in eight different flavors. Similar to algebraic modeling languages like AMPL or GAMS, it includes high-level interfaces to state-of-the-art numerical codes for nonlinear program- ming, quadratic programming and integration of differential- algebraic equations. CasADi is implemented in self-contained C++ code and contains full-featured front-ends to Python and Octave for rapid prototyping. In this paper, we discuss CasADi from the perspective of the developer or advanced user of algorithms for dynamic optimization for the first time, leaving out details on the implementation of the tool. We demonstrate how the tool can be used to model highly complex dynamical systems directly or import existing models formulated in the algebraic modeling language AMPL or the physical modeling language Modelica. Given this symbolic representation of the process models, the resulting optimal control problem can be solved using a vari- ety of methods, including transcription methods (collocation), methods with embedded integrators (multiple shooting) as well as indirect methods.
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| 9. |
- Filieri, Antonio, et al.
(author)
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Autotuning control structures for reliability-driven dynamic binding
- 2012
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In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - 0743-1546. - 9781467320658 ; , s. 418-423
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Conference paper (peer-reviewed)abstract
- This paper explores a formally grounded ap- proach to solve the problem of dynamic binding in service- oriented software architecture. Dynamic binding is a widely adopted mean to automatically bind exposed software interfaces to actual implementations. The execution of an operation on one or another implementation, though providing the same result, could turn out in different quality of service, e.g. due to failure occurrence. Dynamic binding is thus of primary importance to achieve what in the Software Engineering domain is called “self- adaptiveness”, the capability to preserve a desired quality of service, if this is feasible. It is important to reach this goal also in the presence of environmental fluctuations – a route congestion increase – or even abrupt variations – a server breakdown. A quite general dynamic binding problem is here reformulated as a discrete-time feedback control one, and the use of autotuning techniques is discussed, extending previous research, in a view to guaranteeing the desired quality of service without the need for computationally-intensive optimisations.
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| 10. |
- Heemels, W.P.M.H, et al.
(author)
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An introduction to event-triggered and self-triggered control
- 2012
-
In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - : IEEE conference proceedings. - 9781467320641 ; , s. 3270-3285
-
Conference paper (peer-reviewed)abstract
- Recent developments in computer and communication technologies have led to a new type of large-scale resource-constrained wireless embedded control systems. It is desirable in these systems to limit the sensor and control computation and/or communication to instances when the system needs attention. However, classical sampled-data control is based on performing sensing and actuation periodically rather than when the system needs attention. This paper provides an introduction to event- and self-triggered control systems where sensing and actuation is performed when needed. Eventtriggered control is reactive and generates sensor sampling and control actuation when, for instance, the plant state deviates more than a certain threshold from a desired value. Selftriggered control, on the other hand, is proactive and computes the next sampling or actuation instance ahead of time. The basics of these control strategies are introduced together with a discussion on the differences between state feedback and output feedback for event-triggered control. It is also shown how event- and self-triggered control can be implemented using existing wireless communication technology. Some applications to wireless control in process industry are discussed as well.
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| 11. |
- Jakobsson, Martin, 1986-, et al.
(author)
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A Comparative Analysis of the Fast-Lipschitz Convergence Speed
- 2012
-
In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 7464-7469
-
Conference paper (peer-reviewed)abstract
- Fast-Lipschitz optimization is a recently proposed framework useful for an important class of centralized and distributed optimization problems over peer-to-peer networks. The properties of Fast-Lipschitz problems allow to compute the solution without having to introduce Lagrange multipliers, as in most other methods. This is highly beneficial, since multipliers need to be communicated across the network and thus increase the communication complexity of solution algorithms. Although the convergence speed of Fast-Lipschitz optimization methods often outperforms Lagrangian methods in practice, there is not yet a theoretical analysis. This paper provides a fundamental step towards such an analysis. Sufficient conditions for superior convergence of the Fast-Lipschitz method are established. The results are illustrated by simple examples. It is concluded that optimization problems with quadratic cost functions and linear constraints are always better solved by Fast-Lipschitz optimization methods, provided that certain conditions hold on the eigenvalues of the Hessian of the cost function and constraints.
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| 12. |
- Lehmann, Daniel, et al.
(author)
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Event-triggered PI control : Saturating actuators and anti-windup compensation
- 2012
-
In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 6566-6571
-
Conference paper (peer-reviewed)abstract
- Event-triggered control aims at reducing the communication load over the feedback link in networked control systems by adapting the information exchange to the current needs. This paper investigates the consequences of actuator saturation on the behavior of event-triggered PI control. Stability properties are derived using linear matrix inequalities (LMIs) which show how the stability of the event-triggered control loop depends on the selection of the event threshold. In order to overcome the potential performance degradation due to integrator windup caused by actuator saturation, the proposed scheme is extended by incorporating a static anti-windup mechanism. The results are illustrated by simulations.
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| 13. |
- Lennartson, Bengt, 1956, et al.
(author)
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Numerical sensitivity of Linear Matrix Inequalities for shorter sampling periods
- 2012
-
In: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. - 9781467320641 ; :Article number 6425801, s. 4247-4252
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Conference paper (peer-reviewed)abstract
- The numerical sensitivity of Linear Matrix Inequalities (LMIs) arising in the H∞ norm computation in discrete time is analyzed. Rapid sampling scenarios are examined comparing both shift and delta operator formulations of the equations. The shift operator formulation is shown in general to be arbitrarily poorly conditioned as the sampling rate increases. The delta operator formulation includes both recentering (to avoid cancellation problems) and rescaling, and avoids these difficulties. However, it is also shown that rescaling of the shift operator formulation gives substantial improvements in numerical conditioning, whilst recentering is of more limited benefit.
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| 14. |
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| 15. |
- Murgovski, Nikolce, 1980, et al.
(author)
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Dimensioning and Control of a Thermally Constrained Double Buffer Plug-in HEV Powertrain
- 2012
-
In: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. - 9781467320658 ; , s. 6346-6351
-
Conference paper (peer-reviewed)abstract
- This paper describes modeling steps to enable fast evaluation of performance and cost effectiveness of a plugin hybrid electric vehicle. The paper also shows how convex optimization can be used to dimension the vehicle powertrain while simultaneously controlling the energy buffer power. The method allows for optimal control of powertrain components that are subject to thermal constraints. The studied vehicle is a city bus driven along a perfectly known bus line. The bus is equipped with an engine-generator unit and an energy buffer consisting of an ultracapacitor and a battery. The engine generator unit and the energy buffer are modeled with quadratic power losses and are sized for two different charging scenarios. In the first scenario the bus can charge for a couple of seconds while standing still at bus stops, and in the second scenario the bus can charge for a couple of minutes before starting the route. In both scenarios, the ultracapacitor temperature is kept below a certain limit.
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| 16. |
- Park, Pangun, et al.
(author)
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Delay distribution analysis of wireless personal area networks
- 2012
-
In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - : IEEE conference proceedings. - 9781467320641 ; , s. 5864-5869
-
Conference paper (peer-reviewed)abstract
- Characterizing the network delay distribution is a fundamental step to properly compensate the delay of Networked Control Systems (NCSs). Due to the random backoff mechanism employed by Wireless Personal Area Network (WPAN) protocols, it is difficult to derive such a distribution. In this paper, the probability distribution of the delay for successfully received packets in WPANs is characterized. The analysis uses a moment generating function method based on an extended Markov chain model. The model considers the exponential backoff process with retry limits, acknowledgements, unsaturated traffic, and variable packet size, and gives an accurate explicit expression of the probability distribution of the network delay. The probability distribution of the delay is a function of the traffic load, number of nodes, and parameters of the communication protocol. Monte Carlo simulations validate the analysis for different network and protocol parameters. We show that the probability distribution of the delay is significantly different from existing network models used for NCS design. Furthermore, the parameters of the communication protocol result to be critical to stabilize control systems.
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| 17. |
- Pettersson, Anders, et al.
(author)
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Analysis of Linear L1 Adaptive Control Architectures for Aerospace Applications
- 2012
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In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - 0743-1546. - 9781467320658 ; , s. 1136-1141
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Conference paper (peer-reviewed)abstract
- In some situations the closed-loop system obtained by L1 adaptive control is equivalent to linear systems. The architectures of these systems are investigated and compared with internal model control and the input observer architecture. The analysis is focused on aerospace application. An effort has been made to understand and describe what fundamental control characteristic of flying applications that make L1 adaptive controllers suitable for the task.
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| 18. |
- Ramesh, Chithrupa, et al.
(author)
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Stability analysis of multiple state-based schedulers with CSMA
- 2012
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In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 7205-7211
-
Conference paper (peer-reviewed)abstract
- In this paper, we identify sufficient conditions for Lyapunov Mean Square Stability (LMSS) of a contention-based network of first-order systems, with state-based schedulers. The stability analysis helps us to choose policies for adapting the scheduler threshold to the delay from the network and scheduler. We show that three scheduling laws can result in LMSS: constant-probability laws and additively increasing or decreasing probability laws. Our results counter the notions that increasing probability scheduling laws alone can guarantee stability of the closed-loop system, or that decreasing probability scheduling laws are required to mitigate congestion in the network.
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| 19. |
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| 20. |
- Shi, Guodong, et al.
(author)
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Persistent graphs and consensus convergence
- 2012
-
In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 2046-2051
-
Conference paper (peer-reviewed)abstract
- This paper investigates the role persistent arcs play for averaging algorithms to reach a global consensus under discrete-time or continuous-time dynamics. Each (directed) arc in the underlying communication graph is assumed to be associated with a time-dependent weight function. An arc is said to be persistent if its weight function has infinite ℒ1 or ℓ1 norm for continuous-time or discrete-time models, respectively. The graph that consists of all persistent arcs is called the persistent graph of the underlying network. Three necessary and sufficient conditions on agreement or ε-agreement are established, by which we prove that the persistent graph fully determines the convergence to a consensus. It is also shown how the convergence rates explicitly depend on the diameter of the persistent graph.
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| 21. |
- Shi, Guodong, et al.
(author)
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Randomized Gossiping with Unreliable Communication : Dependent or Independent Node Updates
- 2012
-
In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 4846-4851
-
Conference paper (peer-reviewed)abstract
- This paper studies an asynchronous randomized gossip algorithm under unreliable communication. At each instance, two nodes are selected to meet with a given probability. When nodes meet, two unreliable communication links are established with communication in each direction succeeding with a time-varying probability. It is shown that two particularly interesting cases arise when these communication processes are either perfectly dependent or independent. Necessary and sufficient conditions on the success probability sequence are proposed to ensure almost sure consensus or ?-consensus. Weak connectivity is required when the communication is perfectly dependent, while double connectivity is required when the communication is independent. Moreover, it is proven that with odd number of nodes, average preserving turns from almost forever (with probability one for all initial conditions) for perfectly dependent communication, to almost never (with probability zero for almost all initial conditions) for the independent case. This average preserving property does not hold true for general number of nodes. These results indicate the fundamental role the node interactions have in randomized gossip algorithms.
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| 22. |
- Soltesz, Kristian, et al.
(author)
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Simulated Mid-ranging Control of Propofol and Remifentanil using EEG-measured Hypnotic Depth of Anesthesia
- 2012
-
In: 51st IEEE Conference on Decision and Control. - 0191-2216. - 9781467320641 ; , s. 356-361
-
Conference paper (peer-reviewed)abstract
- This paper suggests an extension of an existing, clinically evaluated, closed-loop drug delivery system for hypnotic depth control using propofol. The extension introduces closed-loop administration of the analgesic drug remifentanil, thus forming a multiple input–single output (MISO) control system. Remifentanil acts and is metabolized at a significantly faster time scale than propofol. Direct control of analgesia is hindered by the current absence of a reliable real-time nociception monitor. However, several hypnotic depth monitors respond to nociception. Sudden changes in the measured hypnotic depth are frequently caused by changes in noxious stimulation. The novelty of this work lies in increasing the disturbance rejection bandwidth of the control system for hypnotic depth by directing the high frequency content of its control error to a remifentanil controller. Such a mid-ranging control system was implemented and tuned based on 23 patient models obtained from a previous clinical study and its performance is demonstrated through a simulation study.
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| 23. |
- Sootla, Aivar, et al.
(author)
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Scalable Positivity Preserving Model Reduction Using Linear Energy Functions
- 2012
-
In: IEEE 51st Annual Conference on Decision and Control (CDC), 2012. - 0743-1546. - 9781467320658 ; , s. 4285-4290
-
Conference paper (peer-reviewed)abstract
- In this paper, we explore positivity preserving model reduction. The reduction is performed by truncating the states of the original system without balancing in the classical sense. This may result in conservatism, however, this way the physical meaning of the individual states is preserved. The reduced order models can be obtained using simple matrix operations or using distributed optimization methods. Therefore, the developed algorithms can be applied to sparse large-scale systems.
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| 24. |
- Stankovic, Milos S., et al.
(author)
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Distributed calibration for sensor networks under communication errors and measurement noise
- 2012
-
In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 1380-1385
-
Conference paper (peer-reviewed)abstract
- In this paper a new distributed calibration algorithm based on consensus is proposed for sensor networks. The algorithm is basically formulated as a set of stochastic gradient type recursions for estimating parameters of local sensor calibration functions, starting from local criteria defined as weighted sums of mean square errors between the outputs of neighboring sensors. It is proved that the proposed algorithm provides asymptotic consensus in the space of the sensor gains and offsets. In the case of communication dropouts and additive communication and measurement noise, a modification of the instrumental variable type of the original calibration scheme is proposed. It is proved using stochastic approximation arguments that in this case the proposed algorithm achieves asymptotic consensus in the mean square sense and with probability one. Some illustrative simulation examples are provided.
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| 25. |
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| 26. |
- Terelius, Håkan, et al.
(author)
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Distributed size estimation of dynamic anonymous networks
- 2012
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In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467320641 ; , s. 5221-5227
-
Conference paper (peer-reviewed)abstract
- We consider the problem of estimating the size of dynamic anonymous networks, motivated by network maintenance. The proposed algorithm is based on max-consensus information exchange protocols, and extends a previous algorithm for static anonymous networks. A regularization term is accounting for a-priori assumptions on the smoothness of the estimate, and we specifically consider quadratic regularization terms since they lead to closed-form solutions and intuitive design laws. We derive an explicit estimation scheme for a particular peer-to-peer service network, starting from its statistical model. To validate the accuracy of the algorithm, we perform numerical experiments and show how the algorithm can be implemented using finite precision arithmetics as well as small communication burdens
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| 27. |
- Wu, Junfeng, et al.
(author)
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An improved hybrid sensor schedule for remote state estimation under limited communication resources
- 2012
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In: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on. - : IEEE conference proceedings. - 9781467320641 ; , s. 3305-3310
-
Conference paper (peer-reviewed)abstract
- In this paper, we consider remote state estimation. A sensor locally processes its measurement data and sends its local estimate to a remote estimator for further processing. Due to the limited communication resources, the sensor can only communicate with the estimator for a pre-specified number within a given horizon. We propose a hybrid sensor data schedule which introduces an event-triggering mechanism on top of an optimal offline sensor schedule. This hybrid schedule, having a small implementation cost, leads to a smaller estimation error at the remote estimator when compared with the optimal offline sensor schedule.
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